> ## Documentation Index
> Fetch the complete documentation index at: https://docs.unstructured.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Astra DB
Connect Astra DB to your preprocessing pipeline, and use the Unstructured Ingest CLI or the Unstructured Ingest Python library to batch process all your documents and store structured outputs locally on your filesystem.
The requirements are as follows.
* An IBM Cloud account or DataStax account.
* For an IBM Cloud account, [sign up](https://cloud.ibm.com/registration) for an IBMid, and then [sign in](https://accounts.datastax.com/session-service/v1/login) to DataStax with your IBMid.
* For a DataStax account, [sign up](https://astra.datastax.com/signup) for a DataStax account, and then [sign in](https://accounts.datastax.com/session-service/v1/login) to DataStax with your DataStax account.
* An Astra DB database in the DataStax account. To create a database:
a. After you sign in to DataStax, click **Create database**.
b. Click the **Serverless (vector)** tile, if it is not already selected.
c. For **Database name**, enter some unique name for the database.
d. Select a **Provider** and a **Region**, and then click **Create database**.
[Learn more](https://docs.datastax.com/en/astra-db-classic/databases/manage-create.html).
* An application token for the database. To create an application token:
a. After you sign in to DataStax, in the list of databases, click the name of the target database.
b. On the **Overview** tab, under **Database Details**, in the **Application Tokens** tile, click **Generate Token**.
c. Enter some **Token description** and select and **Expiration** time period, and then click **Generate token**.
d. Save the application token that is displayed to a secure location, and then click **Close**.
[Learn more](https://docs.datastax.com/en/astra-db-serverless/administration/manage-application-tokens.html).
* A keyspace in the database. To create a keyspace:
a. After you sign in to DataStax, in the list of databases, click the name of the target database.
b. On the **Data Explorer** tab, in the **Keyspace** list, select **Create keyspace**.
c. Enter some **Keyspace name**, and then click **Add keyspace**.
[Learn more](https://docs.datastax.com/en/astra-db-serverless/databases/manage-keyspaces.html#keyspaces).
* A collection in the keyspace.
For the [Unstructured UI](/ui/overview) and [Unstructured API](/api-reference/overview):
* An existing collection is not required. At runtime, the collection behavior is as follows:
* If an existing collection name is specified, and Unstructured generates embeddings,
but the number of dimensions that are generated does not match the existing collection's embedding settings, the run will fail.
You must change your Unstructured embedding settings or your existing collection's embedding settings to match, and try the run again.
* If a collection name is not specified, Unstructured creates a new collection in your keyspace. If Unstructured generates embeddings,
the new collection's name will be `u__`.
If Unstructured does not generate embeddings, the new collection's name will be `u
b. On the **Data Explorer** tab, in the **Keyspace** list, select the name of the target keyspace.
c. In the **Collections** list, select **Create collection**.
d. Enter some **Collection name**.
e. Turn on **Vector-enabled collection**, if it is not already turned on.
f. Choose a mode for **Embedding generation method**. See [Astra DB generated embeddings](#astra-db-generated-embeddings).
g. If you chose **Bring my own**, enter the number of dimensions for the embedding model that you plan to use.
h. For **Similarity metric**, select **Cosine**.
i. Click **Create collection**.
[Learn more](https://docs.datastax.com/en/astra-db-serverless/databases/manage-collections.html#create-collection).
The Astra DB connector dependencies:
```bash CLI, Python theme={null}
pip install "unstructured-ingest[astradb]"
```
You might also need to install additional dependencies, depending on your needs. [Learn more](/open-source/ingestion/ingest-dependencies).
These environment variables:
* `ASTRA_DB_API_ENDPOINT` - The API endpoint for the Astra DB database, represented by `--api-endpoint` (CLI) or `api_endpoint` (Python). To get the endpoint, see the **Database Details > API Endpoint** value on your database's **Overview** tab.
* `ASTRA_DB_APPLICATION_TOKEN` - The database application token value for the database, represented by `--token` (CLI) or `token` (Python). To get the token, see the **Database Details > Application Tokens** box on your database's **Overview** tab.
* `ASTRA_DB_KEYSPACE` - The name of the keyspace for the database, represented by `--keyspace` (CLI) or `keyspace` (Python).
* `ASTRA_DB_COLLECTION` - The name of the collection for the keyspace, represented by `--collection-name` (CLI) or `collection_name` (Python). If no value is provided, see the beginning of this article for the behavior at run time.
Additional settings include:
* For the source connector only, `--fields` (CLI) or `fields` (Python): Optionally, a comma-separated list (CLI) or an array of strings (Python) of fields
to include in the output. The default is to include all fields, if not otherwise specified.
* For the destination connector only, `--flatten-metadata` (CLI) or `flatten_metadata=True` (Python): Optionally, whether to "flatten" the metadata. Specifically, the metadata key values are
brought to the top level of the element, and the `metadata` key itself is removed. To not flatten the metadata (the default), specify `--no-flatten_metadata` (CLI) or
`flatten_metadata=False` (Python). The default is is to not flatten the metadata if not otherwise specified.
* For the destination connector only, `--binary-encode-vectors` (CLI) or `binary_encode_vectors=True` (Python): Optionally, control when to upload vectors in a binary format. By default, vectors are binary encoded (`true`), which is more efficient. To upload vectors as a human-readable list of floats instead, specify `--no-binary-encode-vectors` (CLI) or `binary_encode_vectors=False` (Python). **WARNING**: Disabling this option may make the upload slower!
* For the destination connector only, `--enable-lexical-search` (CLI) or `enable_lexical_search=True` (Python): Optionally, enable lexical and hybrid search.
* For the destination connector only, `--astra-generated-embeddings` (CLI) or `astra_generated_embeddings=True` (Python): Optionally, use an Astra vectorize integration for embeddings.
Now call the Unstructured CLI or Python. The destination connector can be any of the ones supported. This example uses the local destination connector.
This example sends data to Unstructured for processing by default. To process data locally instead, see the instructions at the end of this page.
```bash CLI theme={null}
#!/usr/bin/env bash
unstructured-ingest \
astradb \
--api-endpoint $ASTRA_DB_API_ENDPOINT \
--token $ASTRA_DB_APPLICATION_TOKEN \
--collection-name $ASTRA_DB_COLLECTION \
--keyspace $ASTRA_DB_KEYSPACE \
--fields record_id,content \
--download-dir $LOCAL_FILE_DOWNLOAD_DIR \
--partition-by-api \
--api-key $UNSTRUCTURED_API_KEY \
--partition-endpoint $UNSTRUCTURED_API_URL \
--additional-partition-args="{\"split_pdf_page\":\"true\", \"split_pdf_allow_failed\":\"true\", \"split_pdf_concurrency_level\": 15}"
```
```python Python Ingest theme={null}
import os
from unstructured_ingest.pipeline.pipeline import Pipeline
from unstructured_ingest.interfaces import ProcessorConfig
from unstructured_ingest.processes.connectors.astradb import (
AstraDBIndexerConfig,
AstraDBDownloaderConfig,
AstraDBConnectionConfig,
AstraDBAccessConfig
)
from unstructured_ingest.processes.connectors.local import LocalConnectionConfig
from unstructured_ingest.processes.partitioner import PartitionerConfig
from unstructured_ingest.processes.chunker import ChunkerConfig
from unstructured_ingest.processes.embedder import EmbedderConfig
# Chunking and embedding are optional.
if __name__ == "__main__":
Pipeline.from_configs(
context=ProcessorConfig(),
indexer_config=AstraDBIndexerConfig(
collection_name=os.getenv("ASTRA_DB_COLLECTION"),
keyspace=os.getenv("ASTRA_DB_KEYSPACE"),
batch_size=20
),
downloader_config=AstraDBDownloaderConfig(
download_dir=os.getenv("LOCAL_FILE_DOWNLOAD_DIR"),
fields=["record_id", "content"]
),
source_connection_config=AstraDBConnectionConfig(
access_config=AstraDBAccessConfig(
api_endpoint=os.getenv("ASTRA_DB_API_ENDPOINT"),
token=os.getenv("ASTRA_DB_APPLICATION_TOKEN")
)
),
partitioner_config=PartitionerConfig(
partition_by_api=True,
api_key=os.getenv("UNSTRUCTURED_API_KEY"),
partition_endpoint=os.getenv("UNSTRUCTURED_API_URL"),
additional_partition_args={
"split_pdf_page": True,
"split_pdf_allow_failed": True,
"split_pdf_concurrency_level": 15
}
),
chunker_config=ChunkerConfig(chunking_strategy="by_title"),
embedder_config=EmbedderConfig(embedding_provider="huggingface"),
destination_connection_config=LocalConnectionConfig()
).run()
```
For the Unstructured Ingest CLI and the Unstructured Ingest Python library, you can use the `--partition-by-api` option (CLI) or `partition_by_api` (Python) parameter to specify where files are processed:
* To do local file processing, omit `--partition-by-api` (CLI) or `partition_by_api` (Python), or explicitly specify `partition_by_api=False` (Python).
Local file processing does not use an Unstructured API key or API URL, so you can also omit the following, if they appear:
* `--api-key $UNSTRUCTURED_API_KEY` (CLI) or `api_key=os.getenv("UNSTRUCTURED_API_KEY")` (Python)
* `--partition-endpoint $UNSTRUCTURED_API_URL` (CLI) or `partition_endpoint=os.getenv("UNSTRUCTURED_API_URL")` (Python)
* The environment variables `UNSTRUCTURED_API_KEY` and `UNSTRUCTURED_API_URL`
* To send files to the legacy [Unstructured Partition Endpoint](/api-reference/legacy-api/partition/overview) for processing, specify `--partition-by-api` (CLI) or `partition_by_api=True` (Python).
Unstructured also requires an Unstructured API key and API URL, by adding the following:
* `--api-key $UNSTRUCTURED_API_KEY` (CLI) or `api_key=os.getenv("UNSTRUCTURED_API_KEY")` (Python)
* `--partition-endpoint $UNSTRUCTURED_API_URL` (CLI) or `partition_endpoint=os.getenv("UNSTRUCTURED_API_URL")` (Python)
* The environment variables `UNSTRUCTURED_API_KEY` and `UNSTRUCTURED_API_URL`, representing your API key and API URL, respectively.
You must specify the API URL only if you are not using the default API URL for Unstructured Ingest, which applies to **Let's Go**, **Pay-As-You-Go**, and **Business SaaS** accounts.
The default API URL for Unstructured Ingest is `https://api.unstructuredapp.io/general/v0/general`, which is the API URL for the legacy[Unstructured Partition Endpoint](/api-reference/legacy-api/partition/overview). However, you should always use the URL that was provided to you when your Unstructured account was created. If you do not have this URL, email Unstructured Support at [support@unstructured.io](mailto:support@unstructured.io).
If you do not have an API key, [get one now](/api-reference/legacy-api/partition/overview).
If you are using a **Business** account, the process
for generating Unstructured API keys, and the Unstructured API URL that you use, are different.
For instructions, see your Unstructured account administrator, or email Unstructured Support at [support@unstructured.io](mailto:support@unstructured.io).